KINETICS of QUALITY CHANGE DURING COOKING and FRYING of POTATOES: PART II. COLOR
Bibliographic record
Abstract
ABSTRACT Color, as a quality attribute of cooked and fried potatoes, is affected by the extent and nature of heat during thermal processing. Improvement of color parameters has been made possible by the increase in knowledge of kinetics of color change. Analysis of kinetic data allows processors to minimize undesirable changes and optimize color retention. the objective of this study was to evaluate kinetics of color change during cooking and frying of potatoes. Potatoes were cut into cylinders (diameter × height: 20 mm × 20 mm for cooking and 10 mm × 20 mm for frying) and cooked in a temperature controlled water bath at 80–100C or fried in a commercial fryer at 160–190C for selected times. Color changes associated with cooked and fried potatoes were evaluated using a tristiumulus colorimeter in the L, a, b mode. For cooked potatoes, L and b values decreased while ΔE and a values increased with time at each cooking temperature. For fried potatoes, L value decreased while a, b and ΔE values increased as frying time increased. A modified first order model was used to characterize color change kinetics of both cooked and fried potatoes based on changes occurring between the initial and a maximum or minimum value. Temperature sensitivity of rate constants was adequately described by the Arrhenius and z‐value models.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".